MEG源重构的双向正则化方法
A two-way regularization method for MEG source reconstruction
摘要：
脑磁图（MEG）逆问题是指从脑磁图（MEG）测量结果重建大脑的神经活动。我们提出了一种双向正则化（TWR）方法来解决MEG逆问题的假设下，只有少量的位置在空间上负责测量信号（焦点），每个源的时间过程是平滑的时间（平滑）。通过在数据拟合准则中引入稀疏诱导罚分和粗糙罚分，分别保证了重构信号的聚焦性和光滑性。提出了一种两阶段快速算法，第一阶段得到源时间过程的原始估计，第二阶段通过双向正则化对源时间过程进行修正。所提出的方法被证明是有效的合成和现实世界的例子。
英文摘要：
The MEG inverse problem refers to the reconstruction of the neural activity of the brain from magnetoencephalography (MEG) measurements. We propose a two-way regularization (TWR) method to solve the MEG inverse problem under the assumptions that only a small number of locations in space are responsible for the measured signals (focality), and each source time course is smooth in time (smoothness). The focality and smoothness of the reconstructed signals are ensured respectively by imposing a sparsity-inducing penalty and a roughness penalty in the data fitting criterion. A two-stage algorithm is developed for fast computation, where a raw estimate of the source time course is obtained in the first stage and then refined in the second stage by the two-way regularization. The proposed method is shown to be effective on both synthetic and real-world examples.
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